1. Field of the Invention
The present invention relates broadly to the processing of information obtained by an acoustic borehole tool. More particularly, the invention relates to the real-time or post-processing of acoustic wave data to determine the formation velocity and dispersion properties of an acoustic wave propagating along the borehole using a coherence method of acoustic wave data analysis.
2. Description of the Related Art
Acoustic well logging is a well developed art, and details of acoustic logging tools and techniques are set forth in A. Kurkjian, et al., xe2x80x9cSlowness Estimation from Sonic Logging Waveformsxe2x80x9d, Geoexploration, Vol. 277, pp. 215-256 (1991); C. F. Morris et al., xe2x80x9cA New Sonic Array Tool for Full Waveform Logging,xe2x80x9d SPE-13285, Society of Petroleum Engineers (1984); A. R. Harrison et al., xe2x80x9cAcquisition and Analysis of Sonic Waveforms From a Borehole Monopole and Dipole Source . . . xe2x80x9d SPE 20557, pp. 267-282 (September 1990); and C. V. Kimball and T. L. Marzetta, xe2x80x9cSemblance Processing of Borehole Acoustic Array Dataxe2x80x9d, Geophysics, Vol. 49, pp. 274-281 (March 1984), all of which are hereby incorporated by reference herein. An acoustic logging tool typically includes an acoustic source (transmitter), and a set of receivers that are spaced several inches or feet apart. An acoustic signal is transmitted by the acoustic source and received at the receivers of the borehole tool which are spaced apart from the acoustic source. Measurements are repeated every few inches as the tool is drawn up (or down) the borehole. The acoustic signal from source travels through the formation adjacent the borehole to the receiver array, and the arrival times and perhaps other characteristics of the receiver responses are recorded. Typically, compressional wave (P-wave), shear wave (S-wave), and Stoneley wave arrivals and waveforms are detected by the receivers and are processed. The processing of the data is often accomplished uphole or may be processed real time in the tool itself. Regardless, the information that is recorded is typically used to find formation characteristics such as formation slowness (the inverse of acoustic speed), from which pore pressure, porosity, and other formation property determinations can be made. In some tools, the acoustic signals may even be used to image the formation.
Many different techniques are known in the art for processing the acoustic wave signals in order to obtain information regarding the borehole and/or formation. Typically, the processing involves digitizing the received signal at a desired sampling rate and then processing the digitized samples according to desired techniques. Examples may be found in the references cited above, as well as in articles such as A. R. Harrison et al., xe2x80x9cAcquisition and Analysis of Sonic Waveforms From a Borehole Monopole and Dipole Source . . . xe2x80x9d SPE 20557, pp. 267-282 (September 1990).
Compressional slowness has been computed using Slowness-Time Coherence (STC) processing. C. V. Kimball and T. L. Marzetta, xe2x80x9cSemblance Processing of Borehole Acoustic Array Dataxe2x80x9d, Geophysics, Vol. 49, pp. 274-281 (March 1984). In STC processing, the measured signal is time window xe2x80x9cfilteredxe2x80x9d and stacked, and a semblance function is computed. The semblance function relates the presence or absence of an arrival with a particular assumed slowness and particular assumed arrival time. If the assumed slowness and arrival time do not coincide with that of the measured arrival, the semblance takes on a smaller value. Consequently, arrivals in the received waveforms manifest themselves as local peaks in a plot of semblance versus slowness and arrival time. These peaks are typically found in a peak-finding routine discussed in the aforementioned article by Kimball and Marzetta, which is hereby incorporated herein by reference.
Acoustic LWD has many potential applications in oil field services including seismic correlation while drilling, pore pressure and porosity determinations, and mechanical property determinations. Because telemetry cables may not be available in these situations, the transfer of data may be accomplished via the use of pulses in the flow of the drilling mud (i.e., mud pulse telemetry). While the drilling penetration rate is very slow relative to normal logging rates, data acquisition still can far exceed the highest data transmission rates in the mud. Thus, in any proposed acoustic LWD art, processing of data downhole may be highly desirable, although the downhole computing power may be limited. Alternatively, data may be stored in the memory of the downhole tool, but this could require frequent xe2x80x9ctrippingxe2x80x9d of the drill string.
One technique that permits the downhole processing of data with limited computing power is to calculate the semblance function using time windowing and stacking of the measured acoustic signal. However, windowing the signal may result in inaccuracies and nonlinearities based on the window width for the resulting semblance. Extrapolating from the windowed semblance often results in adding new errors and amplifying existing errors.
It would be advantageous if a non-windowed technique could be used to calculate semblance and determine acoustic speed including the formation velocity. It would also be advantageous if these parameters could be calculated using each data point collected, require a minimal amount of processing, and reduce the errors typically occurring in windowed calculations of formation velocity and semblance.
A system and method is provided for characterizing earth formations. In one embodiment, the method includes passing a logging tool through a borehole and repeatedly: (a) triggering an acoustic wave generator; (b) recording acoustic waveforms received by receivers in the logging tool; (c) determining a time semblance (as a function of slowness and time) of the recorded acoustic waveforms; and (d) smoothing the time semblance. In a different embodiment, a phase semblance (as a function of slowness and frequency) of the recorded acoustic waveforms is determined and smoothed. The smoothing may be performed using an adaptive wavelet transform technique or an adaptive moving average filter technique. In each case the average time or frequency spacing between semblance peaks is preferably determined and used to adapt the smoothing operation in a manner that varies with the slowness value s.